Expert systems have evolved out of the work on artificial intelligence over the past few
decades and are finding increasing applications in business. The system gathers together a
database of knowledge or expertise to offer advice or solution for problems in a particular area
by emulating the abilities and judgments of human experts. It accumulates all the expert
knowledge in a given area so that the advice or solution offered is better than that of a single
consultant or expert. It guides users through problems by asking them a set of questions about
the problem. The answers given are checked against the rule base in the system to draw
appropriate conclusions from the problem situation. Expert systems are particularly useful in
dealing with unstructured problems.
Expert system was originally developed to replicate abilities of human experts. The
system captures and stores human knowledge in a area of expertise, called domain, a uses it to
solve problems which other wise requires the help of human experts. The solution suggested by
the system is expected to be superior to that by any single expert.
Expert systems are designed to solve real problems in a particular domain that normally
would require a human expert. It can solve many types of problems. It is designed to solve
some problems very effectively. But it cannot solve every problem one might encounter in an
area.
Developing an expert system involves extracting relevant knowledge from human experts
in the area of problem, called domain experts. Such knowledge is often heuristic in nature. That
is, it is some useful knowledge based on some “rules of thump” rather than absolute certainties.
Acquisition of such rules of thump and storing them in knowledge base are serious tasks in
building a knowledge base. A knowledge engineer does this of knowledge acquisition and
building a knowledge base.
The expert system consists of two major parts: the development environment and the
consultation environment. The expert system builder uses the development environment to build
the components and store expertise into the knowledge base. Non-expert user uses the
consultant environment to get the expert opinion and advice from the expert system.
decades and are finding increasing applications in business. The system gathers together a
database of knowledge or expertise to offer advice or solution for problems in a particular area
by emulating the abilities and judgments of human experts. It accumulates all the expert
knowledge in a given area so that the advice or solution offered is better than that of a single
consultant or expert. It guides users through problems by asking them a set of questions about
the problem. The answers given are checked against the rule base in the system to draw
appropriate conclusions from the problem situation. Expert systems are particularly useful in
dealing with unstructured problems.
Expert system was originally developed to replicate abilities of human experts. The
system captures and stores human knowledge in a area of expertise, called domain, a uses it to
solve problems which other wise requires the help of human experts. The solution suggested by
the system is expected to be superior to that by any single expert.
Expert systems are designed to solve real problems in a particular domain that normally
would require a human expert. It can solve many types of problems. It is designed to solve
some problems very effectively. But it cannot solve every problem one might encounter in an
area.
Developing an expert system involves extracting relevant knowledge from human experts
in the area of problem, called domain experts. Such knowledge is often heuristic in nature. That
is, it is some useful knowledge based on some “rules of thump” rather than absolute certainties.
Acquisition of such rules of thump and storing them in knowledge base are serious tasks in
building a knowledge base. A knowledge engineer does this of knowledge acquisition and
building a knowledge base.
The expert system consists of two major parts: the development environment and the
consultation environment. The expert system builder uses the development environment to build
the components and store expertise into the knowledge base. Non-expert user uses the
consultant environment to get the expert opinion and advice from the expert system.
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